What is difference between edge computing and federated learning?
Federated systems or Fog models, basically push computation from the active system side to server or network side processes. This is commonly used when computationally expensive services are required on limited systems (such as running some AI or augmentation occlusion processing from on phone), allowing for distributed data processing. Here is a good paper on the matter-
https://arxiv.org/abs/1602.05629
What you might be caught up on is edge computing processes and Fog both operate the same. It's just the model differentiating where the services run.